Nitrate is a nutrient and a potent signal that impacts global gene expression in plants. However, the regulatory factors controlling temporal and cell type-specific nitrate responses remain largely unknown. We assayed nitrate-responsive transcriptome changes in five major root cell types of the root as a function of time.
View Article and Find Full Text PDFDeciphering gene regulatory networks (GRNs) is both a promise and challenge of systems biology. The promise lies in identifying key transcription factors (TFs) that enable an organism to react to changes in its environment. The challenge lies in validating GRNs that involve hundreds of TFs with hundreds of thousands of interactions with their genome-wide targets experimentally determined by high-throughput sequencing.
View Article and Find Full Text PDFDynamic reprogramming of gene regulatory networks (GRNs) enables organisms to rapidly respond to environmental perturbation. However, the underlying transient interactions between transcription factors (TFs) and genome-wide targets typically elude biochemical detection. Here, we capture both stable and transient TF-target interactions genome-wide within minutes after controlled TF nuclear import using time-series chromatin immunoprecipitation (ChIP-seq) and/or DNA adenine methyltransferase identification (DamID-seq).
View Article and Find Full Text PDFChromatin modification has gained increased attention for its role in the regulation of plant responses to environmental changes, but the specific mechanisms and molecular players remain elusive. Here, we show that the Arabidopsis () histone methyltransferase SET DOMAIN GROUP8 (SDG8) mediates genome-wide changes in H3K36 methylation at specific genomic loci functionally relevant to nitrate treatments. Moreover, we show that the specific H3K36 methyltransferase encoded by is required for canonical RNA processing, and that RNA isoform switching is more prominent in the deletion mutant than in the wild type.
View Article and Find Full Text PDFCharting a temporal path in gene networks requires linking early transcription factor (TF)-triggered events to downstream effects. We scale-up a cell-based TF-perturbation assay to identify direct regulated targets of 33 nitrogen (N)-early response TFs encompassing 88% of N-responsive Arabidopsis genes. We uncover a duality where each TF is an inducer and repressor, and in vitro cis-motifs are typically specific to regulation directionality.
View Article and Find Full Text PDFThis study exploits time, the relatively unexplored fourth dimension of gene regulatory networks (GRNs), to learn the temporal transcriptional logic underlying dynamic nitrogen (N) signaling in plants. Our "just-in-time" analysis of time-series transcriptome data uncovered a temporal cascade of elements underlying dynamic N signaling. To infer transcription factor (TF)-target edges in a GRN, we applied a time-based machine learning method to 2,174 dynamic N-responsive genes.
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